| /external/adhd/cras/src/server/ |
| input_data.h | 22 struct input_data { struct
30 * Creates an input_data instance for input iodev.
34 struct input_data *input_data_create(void *dev_ptr);
36 /* Destroys an input_data instance. */
37 void input_data_destroy(struct input_data **data);
40 void input_data_set_all_streams_read(struct input_data *data,
44 * Gets an audio area for |stream| to read data from. An input_data may be
59 struct input_data *data,
68 * data - The input_data to mark frames has been read by |stream|.
74 int input_data_put_for_stream(struct input_data *data
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| /external/tensorflow/tensorflow/core/kernels/ |
| spectrogram_convert_test_data.cc | 29 std::vector<std::vector<std::complex<double>>> input_data; local
30 ReadCSVFileToComplexVectorOrDie(input_filename, &input_data);
32 if (!WriteComplexVectorToRawFloatFile(output_filename, input_data)) {
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| colorspace_op.cc | 65 typename TTypes<T, 2>::ConstTensor input_data = input.flat_inner_dims<T>(); variable
71 TensorShape({input_data.dimension(0)}),
76 functor::RGBToHSV<Device, T>()(context->eigen_device<Device>(), input_data,
102 typename TTypes<T, 2>::ConstTensor input_data = input.flat_inner_dims<T>(); variable
105 functor::HSVToRGB<Device, T>()(context->eigen_device<Device>(), input_data,
129 const GPUDevice& d, TTypes<T, 2>::ConstTensor input_data, \
134 const GPUDevice& d, TTypes<T, 2>::ConstTensor input_data, \
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| cudnn_pooling_gpu.cc | 92 auto input_data = AsDeviceMemory(transformed_input.template flat<T>().data(), local
102 ->ThenPoolForward(pooling_desc, input_desc, input_data,
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| eigen_benchmark.h | 51 Scalar* input_data = local
58 device_.memset(input_data, 123, BufferSize(input_dims));
61 Input input(input_data, input_dims);
72 device_.deallocate(input_data);
132 Scalar* input_data = local
139 device_.memset(input_data, 123, BufferSize(input_dims));
142 Input input(input_data, input_dims);
154 device_.deallocate(input_data);
187 Scalar* input_data = local
194 device_.memset(input_data, 123, BufferSize(input_dims))
272 Scalar* input_data = local
[all...] |
| redux_functor.h | 65 const T* input_data = input.template flat<T>().data(); local
81 input_data, outer_dim](Eigen::Index start,
90 auto in = Input(input_data + i * inner_dim, inner_dim);
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| /external/tensorflow/tensorflow/contrib/tensor_forest/kernels/ |
| reinterpret_string_to_float_op.cc | 38 void Evaluate(const Tensor& input_data, Tensor output_data, int32 start,
41 const auto in_data = input_data.unaligned_flat<string>();
54 const Tensor& input_data = context->input(0); variable
57 if (!CheckTensorBounds(context, input_data)) return;
61 context, context->allocate_output(0, input_data.shape(), &output_data));
64 const int32 num_data = static_cast<int32>(input_data.NumElements());
68 Evaluate(input_data, *output_data, 0, num_data);
70 auto work = [&input_data, output_data, num_data](int64 start, int64 end) {
73 Evaluate(input_data, *output_data, static_cast<int32>(start),
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| /external/tensorflow/tensorflow/core/kernels/fuzzing/ |
| one_hot_fuzz.cc | 39 const uint8_t* input_data; variable
46 input_data = data + 3;
52 input_data = data;
62 flat_tensor(i) = input_data[i];
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| /external/tensorflow/tensorflow/lite/examples/python/ |
| label_image.py | 68 input_data = np.expand_dims(img, axis=0) variable
71 input_data = (np.float32(input_data) - args.input_mean) / args.input_std variable
73 interpreter.set_tensor(input_details[0]['index'], input_data)
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| /external/libtextclassifier/lang_id/common/flatbuffers/ |
| model-utils.cc | 102 const flatbuffers::Vector<uint8_t> *input_data = input->data(); local
103 if (input_data == nullptr) {
107 return mobile::StringPiece(reinterpret_cast<const char *>(input_data->data()),
108 input_data->size());
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| /external/tensorflow/tensorflow/compiler/xla/client/lib/ |
| slicing_test.cc | 109 auto input_data = local
116 {input_data.get(), index_data.get()});
123 auto input_data = local
135 {input_data.get(), index_data.get()});
142 auto input_data = local
153 {input_data.get(), index_data.get()});
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| /external/tensorflow/tensorflow/contrib/tensor_forest/hybrid/core/ops/ |
| routing_function_op.cc | 51 .Input("input_data: float")
68 input_data: The training batch's features as a 2-d tensor; `input_data[i][j]`
88 const Tensor& input_data = context->input(0); variable
92 if (input_data.shape().dim_size(0) > 0) {
94 context, input_data.shape().dims() == 2,
95 errors::InvalidArgument("input_data should be two-dimensional"));
99 if (!CheckTensorBounds(context, input_data)) return;
101 const int32 num_data = static_cast<int32>(input_data.shape().dim_size(0));
103 static_cast<int32>(input_data.shape().dim_size(1))
[all...] |
| routing_gradient_op.cc | 46 .Input("input_data: float")
93 const Tensor& input_data = context->input(0); variable
100 const int32 num_data = static_cast<int32>(input_data.shape().dim_size(0));
102 static_cast<int32>(input_data.shape().dim_size(1));
117 const Tensor point = input_data.Slice(i, i + 1);
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| hard_routing_function_op.cc | 52 .Input("input_data: float")
69 Chooses a single path for each instance in `input_data` and returns the leaf
74 input_data: The training batch's features as a 2-d tensor; `input_data[i][j]`
97 const Tensor& input_data = context->input(0); variable
101 if (input_data.shape().dim_size(0) > 0) {
103 context, input_data.shape().dims() == 2,
104 errors::InvalidArgument("input_data should be two-dimensional"));
108 if (!CheckTensorBounds(context, input_data)) return;
110 const int32 num_data = static_cast<int32>(input_data.shape().dim_size(0))
[all...] |
| k_feature_routing_function_op.cc | 54 .Input("input_data: float")
77 input_data: The training batch's features as a 2-d tensor; `input_data[i][j]`
103 const Tensor& input_data = context->input(0); variable
107 if (input_data.shape().dim_size(0) > 0) {
109 context, input_data.shape().dims() == 2,
110 errors::InvalidArgument("input_data should be two-dimensional"));
114 if (!CheckTensorBounds(context, input_data)) return;
116 const int32 num_data = static_cast<int32>(input_data.shape().dim_size(0));
118 static_cast<int32>(input_data.shape().dim_size(1))
[all...] |
| stochastic_hard_routing_function_op.cc | 56 .Input("input_data: float")
73 Samples a path for each instance in `input_data` and returns the
79 input_data: The training batch's features as a 2-d tensor; `input_data[i][j]`
108 const Tensor& input_data = context->input(0); variable
112 if (input_data.shape().dim_size(0) > 0) {
114 context, input_data.shape().dims() == 2,
115 errors::InvalidArgument("input_data should be two-dimensional"));
119 if (!CheckTensorBounds(context, input_data)) return;
121 const int32 num_data = static_cast<int32>(input_data.shape().dim_size(0))
[all...] |
| /external/tensorflow/tensorflow/lite/toco/graph_transformations/ |
| resolve_constant_gather.cc | 31 const std::vector<DataType<Type>>& input_data = local
57 const DataType<Type>* in = input_data.data() + coords_data[i] * stride;
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| resolve_constant_slice.cc | 33 const auto& input_data = input_array.GetBuffer<Type>().data; local
78 input_data[Offset(padded_shape, {in_b, in_h, in_w, in_d})];
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| resolve_reorder_axes.cc | 61 const auto& input_data = input_array.GetBuffer<DataType>().data; local
72 input_data.data(), output_data.data());
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| /external/tensorflow/tensorflow/lite/tools/accuracy/ |
| run_tflite_model_op_test.cc | 50 std::vector<NodeBuilder::NodeOut> input_data; local
52 std::back_inserter(input_data), [&scope](Input model_input) {
60 .Input(input_data)
110 std::vector<NodeBuilder::NodeOut> input_data; local
112 std::back_inserter(input_data), [&scope](Input model_input) {
120 .Input(input_data)
157 std::vector<NodeBuilder::NodeOut> input_data; local
159 std::back_inserter(input_data), [&scope](Input model_input) {
167 .Input(input_data)
|
| /external/libbrillo/brillo/streams/ |
| fake_stream_unittest.cc | 268 std::string input_data = "foobar-baz"; local
269 size_t split_pos = input_data.find('-');
272 stream_->AddReadPacketString({}, input_data.substr(0, split_pos));
273 stream_->AddReadPacketString(one_sec_delay, input_data.substr(split_pos));
282 buffer.resize(input_data.size());
300 EXPECT_EQ(input_data, (std::string{buffer.begin(), buffer.end()}));
|
| /external/tensorflow/tensorflow/compiler/xla/tests/ |
| copy_test.cc | 251 auto input_data = client_->TransferToServer(empty).ConsumeValueOrDie(); local
253 auto actual = ExecuteAndTransfer(&builder, {input_data.get()}, &out_shape)
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| reshape_test.cc | 697 auto input_data = CreateParameterAndTransferLiteral(0, input_literal, "input", local
702 ComputeAndCompareLiteral(&builder, expected, {input_data.get()},
716 auto input_data = CreateParameterAndTransferLiteral(0, input_literal, "input", local
721 ComputeAndCompareLiteral(&builder, expected, {input_data.get()},
736 auto input_data = CreateParameterAndTransferLiteral(0, input_literal, "input", local
747 ComputeAndCompareLiteral(&builder, expected, {input_data.get()},
762 auto input_data = CreateParameterAndTransferLiteral(0, input_literal, "input", local
843 auto input_data = CreateParameterAndTransferLiteral(0, input_literal, "input", local
870 auto input_data = CreateParameterAndTransferLiteral(0, input_literal, "input", local
897 auto input_data = CreateParameterAndTransferLiteral(0, input_literal, "input", local
925 auto input_data = CreateParameterAndTransferLiteral(0, input_literal, "input", local
952 auto input_data = CreateParameterAndTransferLiteral(0, input_literal, "input", local
[all...] |
| /external/tensorflow/tensorflow/contrib/image/kernels/ |
| adjust_hsv_in_yiq_op.cc | 105 auto input_data = input->shaped<float, 2>({channel_count, kChannelSize}); variable
118 [&input_data, &output_data, &tranformation_matrix](
121 const float* p = input_data.data() + start_channel * kChannelSize;
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| /external/tensorflow/tensorflow/lite/kernels/internal/ |
| resize_nearest_neighbor_test.cc | 30 const RuntimeShape& input_shape, const std::vector<T>& input_data,
39 op_params, input_shape, input_data.data(), output_size_shape,
49 std::vector<float> input_data = {1, 2, 3, 4}; local
54 TestReferenceResizeNearestNeighbor(input_shape, input_data, output_size_data,
60 std::vector<uint8> input_data = {1, 2, 3, 4}; local
65 TestReferenceResizeNearestNeighbor(input_shape, input_data, output_size_data,
71 std::vector<float> input_data = {1, 2, 3, 4, 5, 6, 7, 8, 9}; local
76 TestReferenceResizeNearestNeighbor(input_shape, input_data, output_size_data,
82 std::vector<uint8> input_data = {1, 2, 3, 4}; local
87 TestReferenceResizeNearestNeighbor(input_shape, input_data, output_size_data
93 std::vector<uint8> input_data = {1, 2, 3, 4, 5, 6, 7, 8, local
105 std::vector<float> input_data = {1, 2, 3, 4}; local
116 std::vector<uint8> input_data = {1, 2, 3, 4}; local
133 std::vector<float> input_data = {1, 1, 2, 2, 3, 3, 4, 4, local
[all...] |
